Cyanotoxin mixture models: Relating environmental variables and toxin co-occurrence to human exposure risk
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Abstract
Toxic cyanobacterial blooms, often containing multiple toxins, are a serious public health issue. However, there are no known models that predict a cyanotoxin mixture (anatoxin-a, microcystin, saxitoxin). This paper presents two cyanotoxin mixture models (MIX) and compares them to two microcystin (MC) models from data collected in 2016–2017 from three recurring cyanobacterial bloom locations in Kabetogama Lake, Voyageurs National Park (Minnesota, USA). Models include those using near-real-time environmental variables (readily available) and those using additional comprehensive variables (based on laboratory analyses). Comprehensive models (R2 = 0.87 MC; R2 = 0.86 MIX) explained more variability than the environmental models (R2 = 0.58 MC; R2 = 0.57 MIX). Although neither MIX model was a better fit than the MC models, the MIX models produced no false negatives in the calibration dataset, indicating that all observations above regulatory guidelines were simulated by the MIX models. This is the first known use of Virtual Beach software for a cyanotoxin mixture model, and the methods used in this paper may be applicable to other lakes or beaches.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Cyanotoxin mixture models: Relating environmental variables and toxin co-occurrence to human exposure risk |
| Series title | Journal of Hazardous Materials |
| DOI | 10.1016/j.jhazmat.2021.125560 |
| Volume | 415 |
| Year Published | 2021 |
| Language | English |
| Publisher | Elsevier |
| Contributing office(s) | Upper Midwest Water Science Center |
| Description | 125560, 13 p. |
| Country | United States |
| State | Minnesota |
| Other Geospatial | Kabetogama Lake |
| Google Analytic Metrics | Metrics page |